US Airline Tweets Sentiment Analysis

This project explores tweets sent by customers of various US airline in 2015 using natural language processing. The data is carefully cleaned and transformed to numerical values. Various ML models are used to predict the sentiments after handling the imbalance in the dataset. The sentiment analysis is based on the tweets being neutral, positive, and negative.

Objective

Overview of the project

Key steps I have used are:

1) Load Dataset

2) DATA Visualization

3) Data Preprocessing, Cleaning, and Creating

4) Handling Data Imbalnce

5) Model Building and Development - Training/Testing and Cross-Validation